Unleashed from the plodding pace of biological evolution, the children of
our minds will be free to grow to confront immense and fundamental
challenges in the larger universe.
We humans will benefit for a time from their labors, but sooner or later,
like natural children, they will seek their own fortunes while we, their
aged parents, silently fade away...

--Hans Moravec (Mind Children, p.1)

Human beings create machines to do things more quickly and more
efficiently, but some are beginning to believe that our own inventions
may one day become our own children. Are machines capable of being
recognized as living beings?

One of the earliest experiments at simulating life in technology was
a simple mathematical game created by John H. Conway, first published
and popularized during the early 1970's in issues of Scientific American.
He called it "The Game of Life."

The concept of the Game of Life is very simple. The game takes place
over the cells in an array, like squares on a chessboard. Each cell
can have an organism living inside it or not living inside it; or
each cell itself can be alive or dead. Whatever frame of thought is used,
each cell is described to be "on" or "off."
At the beginning of the game, a certain number
of cells are filled.

Then the game begins. Every clock-tick, a new generation of cells is
created. A set of rules is applied to each cell in the array to
determine what will happen to the cell in this next generation.
The rules are as follows:

If a cell is off and has three neighbors around it which are
on, then the cell becomes on.

If a cell is on and has one or less neighbors around it which
are on, the cell
dies of loneliness (it becomes off).

If a cell is on and has more than three neighbors around it which
are on, the cell dies of overcrowding.

When put in effect over several generations, these simple rules create an
infinite amount of beautiful designs, each design based on the structure of
the cells which are alive at the beginning of the game. To see this in
action, one can experiment with the Lifey Java Applet below.

Lifey is fairly simple to use:

Simply click on the black area above the
controls to turn cells on or off, and then click on the Start button to
begin the generation cycle.

Click on the Pause button (it's where
the Start button used to be) to pause the generation cycle.

Click on the Step button to calculate only one generation.

Click the
Clear button to turn off all the cells in the array.

Adjust the speed
of the generation cycle by moving the Life-cycle speed scrollbar.
Positioning the bar more to the left results in slower speed.

Click on Save to save the
current array, and Load to load the saved array. This is useful if you
want to create a design, test it out, and then load the design and modify
it, etc...

The Use decay algorithm checkbox turns on a simple exponential-based
decay function which causes cells which are off to slowly decay rather than
immediately die; the level of decay is depicted by the shading of the cell.
This option can be used to make the simulation appear more mesmerizing.

Note: Lifey v2.1 uses a torus-based array, which means that the cells at the
edges of the field "wrap around" to the opposite side.

Following are a few cell diagrams which produce interesting results.

Block

Bug

Clock

Glider

R-pent.

Spaceship

X-mastree

Tri-line

Wug

Brokenpog

Greatbig p

This kind of algorithm in which an array of cells exists and its evolution is controlled
by simple mathematical rules belongs to a field of study called Cellular Automata. Although
what is created by Conway's Cellular Automata algorithm does indeed
seem life-like, it is merely an algorithm. But couldn't the process of
thinking which humans go through every day also be considered an algorithm?
Human thought can be described as an algorithm which constantly changes
because it is the
product of millions of other algorithms which constantly change; but it is an algorithm
nevertheless. In this way,
not only Conway's Game of Life, but any computer program (including the
operating system itself) could be considered to have thought, since
they are all based upon algorithms. Although
the level of thought it possesses is not of a very high magnitude,
since its algorithm
is static throughout its entire life-span.

The Premise of Artificial Life
It is this concept of viewing digital technology as a direct analog to biology which is the basis
for the study of artificial life. This field of study became of interest because biologists
thought of it as a new way to learn about life itself: instead of finding out about what life
is by dissecting and taking apart things which are already living, artificial life strives
to build life itself from the ground-up. Thus the approach of study is synthetic rather
than reductionist (Ray 1994).

The major advantage of looking at life from this perspective is that by recreating life
in a different medium, we are not limited to our own system of carbon-based life. Biology
is the study of life, but on Earth we only have access to carbon-based life; and
trying to define life by examining only carbon-based life is like trying to derive
general principles from specific examples. Thus, when we examine the organisms of
our planet, we can discover the things which define life on our planet but not universal
life in general. For this reason, building life from its very basic building blocks--the things
we know that life requires such as an energy source--might help us in finding out the
principles and characteristics of life in general. Thus we can have a broader,
more diverse base of
information from which we can better understand what life truly is (Langton 1992).

In addition to providing new ways to study the biological phenomena associated with life here on Earth,
life-as-we-know-it, Artificial Life allows us to extend our studies to the larger domain of "bio-logic" of possible life,
life-as-it-could-be...

--Chris G. Langton (Artificial Life II, pg. xviii)

Other advantages of this synthetic approach towards biology can be seen by examining
its analog in chemistry, which is a field of study known as synthetic chemistry. Synthetic
chemistry is the ability to create and put together chemical compunds which are not found
in nature; it has given us the ability not only better understand the theory of chemical
phenomena, but it has also allowed us to create new materials and chemicals which are
of great use to industry and technology. In this way, artificial life as well
has been of great use to technology in the fields of computers, robotics, medicine,
nanotechnology, and other areas (Langton 1992).

Examples of Artificial Life
One such program which attempts to create an environment for digital organisms is
Tierra by Tom Ray. Tierra is a computer program which creates a "virtual computer" in
memory--that is, it's a program which creates its own kind of "computer within a computer,"
with its own machine instructions (e.g., its own assembly code) and memory management and
such. Digital organisms are then created within this virtual computer through genetic
programming, which was described in the Genetic Algorithms section of this project: they
are stored as a genome, or a string of bits, and their genome is "brought to life" as an
organism by the virtual computer executing those strings of bits by translating them into
its own machine instructions. This is essentially analogous to the process in biological
life when a protein is synthesized from a DNA strand and it goes on to perform some function,
then bind to a site on the DNA and invoke the production of another protein; it is this
translation from information into action which constitutes the birth and growth of an
organism. These artificial organisms then live in a digital world: they compete for an
energy source, which is CPU time (e.g., how much percentage of the virtual CPU's processing
power per unit of time it gives entirely to an organism), and their material resource (e.g.,
their living space) is the memory of this virtual computer. It is this memory which
contains their machine code, and it is this code which exploits CPU time so that the
organism may reproduce faster than the other organsims.

What results from this simulation is both optimization and creativity of the
organisms. It has been shown in Tierra that, from a single ancestral organism, several
other organisms evolve, some of which are parasitic in nature, some which cooperate with
other organisms, some which deceive. Other organsims react to these changes in their
environment, and through Darwinian natural selection, certain species prevail--for
example, some organisms may develop immunity to parasites--and certain species run into
extinction. Everything the organisms do is controlled by the organism itself (not
"simulated"), and so even the way they reproduce is engraved within their genome. Thus
certain organisms reproduce with different levels of mutation and crossover in their
offspring. As one can see, because everything the organism does is within its genome,
it is possible for the organisms to evolve a great deal of complexity and creativity. This
is very similar to biological life, and behavior of certain Tierra-based systems has
given us more insight into the way life as a whole can evolve and function (Heitkoetter, Joerg and Beasley, Daveid, 1995).

Another AI program, Steen Rasmussen's VENUS, is somewhat similar to Tierra. In VENUS,
genetically-programmed digital organisms occupy memory, and each block of memory has a
specific "resource value" to it--it can vary from a desert (very few resources) to a
jungle (many resources); this resource value is added at a steady state, analogous to
an external energy source such as sunlight. These digital organisms compete for this
memory space and use it for energy, and to go on "living" they must have enough resources
to sustain themselves and their growth (Heitkoetter, Joerg and Beasley, Daveid, 1995).
(VENUS was actually inspired from a concept by
A.K. Dewney called "Core Wars" in which programmers created programs which competed for
the computer's core memory)

Another form of artificial life involves the idea of complex systems, in which small, simple
digital "particles" interact in a very complex way to produce results which are bigger
than the sum of their parts. This field, however, is far to intricate to
delve into in respect to the scope of this project, so we will leave it at that.

Yet another concept which can be a form of artificial life (but is not always
used to implement artificial life) is the idea of the Artifical Neural Network (ANN). ANN's
try to emulate Biological Neural Networks, which are the processes that go on within our
brain when we have thoughts and perform actions: e.g., when one neuron fires off another neuron, and so on.
Although the ANN has no universally accepted definition because of the varieties of it
which exist, most would agree on a few basic things. The ANN is generally made up of
many simple processors, or "units" (these are analogoous to neurons), each of which might
have a certain amount of local memory workspace. Each unit is connected through communication
channels, or "connections" (these are analogoous to dendrites, which connect neurons to one
another) and numeric data is sent between these connections. When this data is sent through,
it is analogous to the biological process of synapsis, when one neuron connects with another
and exchanges information. Each unit is only able to operate on the data it receives from
connections, as well as its local data, and it can also output data. Most ANN's have a
sort of "training rule" in which the weights of connections are adjusted on the basis of
data (Sarle, 1997). This generally allows for an ANN to "learn" from
examples, as a human would be able to identify what any leaf is from examples of
specific leaves. This is amazing because it actually evokes pattern-recognition in humans.
This idea, known as Praxis to the ancient Greeks, was considered by Plato to be one
of the ideas fundamental for human thought processes.

Virtual Pets

The Tamagotchi, a Japanese brand of virtual pet.Photograph courtesy Maido Online.

One product that we daresay might qualify as a very low-level of artificial life
is the so-called "Virtual Pets" which have recently been invading the lives of
youths across the world. These virtual organisms cannot reproduce, nor can they
adapt in creative and evolutionary ways in the true sense of "evolution," but they
do attempt to evolve in a predefined, case-based way indicative of the conditions of the
environment which the "parent" provides (if you want to see a chart of the few possible "outcomes"
that a virtual pet called the Tamagotchi can have, click here). Although these virtual pets could hardly
be classified as artificial life now, it is not hard at all to imagine a time in the
near future when these little toys might have something in the way of built-in infrared transcievers
which allow them to communicate and interact with other virtual pets and actually
evolve in an adaptive and social way, similar to organisms in the Tierra and VENUS a-life systems.
Perhaps each virtual pet will even have its own hard-wired genome which makes it unique
from all the others; the limits of something like this are bounded only by the limits
of the research of synthetic life, which are, in a word, limitless. But it can still be
somewhat depressing to see how much consumerism takes advantage of this radical new
way of thinking.

The Turing Test and Natural Language Processing

Alan Turing in 1951. Photograph courtesy The Alan Turing Scrapbook.

One of the proponents of artificial intelligence was a man who lived in the first half
of this century by the name of Alan Turing. Turing was a visionary who believed that
imitation is reality--that is, if one believes something which is an imitation to be "the
real thing", then that imitation is the real thing. In 1950, he proposed a test
in which a judge would sit at a computer terminal and communicate through it with two other participants--one
a human, the other a machine. If the judge could not tell which one of the participants
was the machine, then the machine was deemed to be intelligent.

This kind of test was obviously not possible at the time because computers had not been
developed to a sufficiently powerful level to even be able to implement keyboards. However,
this kind of test, now well-known as the Turing Test, became possible in the late 1970's
and 1980's with the advent of the personal microcomputer. Starting in 1991, a competition
for whoever's computer program could best "pass" the Turing Test was held, and the winner
was to receive an award formally known as The Loebner Prize (named after Hugh Loebner, who
founded the contest).

Thus far, even the winners of the Loebner Prize have not been extremely convincing as
intelligent machines. So far, most of the implementations for the contest have consisted
of simple algorithms which are able to parse whatever the judge
types in, apply it to a generalized concept through case-based reasoning, and output a pre-written answer
which corresponds to the judge's generalized input. Here you can see the transcript of
the 1997 Loebner Prize winner, written by David Levy. Another turing-style program by
Mark Humphrys can be seen here. You can also try out the 4th place winner of the 1994
Loebner Prize competition, Julia (login as "julia"),
or its winner, a program called Sex, by Thomas Whalen.

Artificial Intelligence obviously still has a long way to go in this field, and we believe that
the answer lies not in case-based reasoning to a particular topic, but rather in the building
of artificial life from the ground-up through ANN's and other evolutionary algorithms discussed before.

Self-consciousness for Computers

Data, the android capable of self-consciousness and (sometimes) emotion, from Star Trek: The Next Generation. Photograph courtesy Paramount Pictures.

So, the question remains: in the end, will computers be capable of self-consciousness,
and are they to be treated as "alive?" Some Kantanists (followers of Emmanuel Kant)
might argue that because consciousness is a prequisite of thought, it is automatically
"biased" by it and cannot be examined objectively. In our own words, examining thought and
consciousness
using one's own thought and consciousness is like using an
instrument to measure a substance, when the instrument fundamentally changes the
perception of the substance itself (and thus the measurement is improper). In this way,
perhaps the intricacies of human consciousness can never be discovered; in short, because
it is the a priori assumptions of the mind which make science possible.

Surely, it would be easy for a programmer to implement a kind of "self-consciousness placebo"
in a Turing-style application through case-based reasoning and the use of variables for
emotions. For example, there could be one variable called "anger" which ranged from 0 to 1.0,
0 being completely calm and complacent, 1.0 being utterly angry. These variables could be
interpreted by the program to evoke text based on the value of the variable, such as
a range of greetings from "hello there" (a value of, say, 0.0) to "what the hell do you want" (value of 0.5) to
"get out of my sight" (value of 1.0). But all of this is still case-based and does not allow
for the biological principle of creativity. Perhaps if this were combined with other AI
concepts such as neural nets and genetic programming, a better "kind" of self-consciousness
could arise.

One so-called "scoffer" of the possibility of self-conscious digital life is Roger Penrose.
A professor of mathematics at Oxford, Penrose believes that consciousness springs from
quantum mechanics--a very complex, mystical, and downright weird field of study. It
consists of the idea of
probability waves, in which any subatomic particle is actually moving in all possible paths
at once (dictated by its "wave function") and if and when it is detected, its wave function collapses and its particle nature
emerges. In this way, quantum mechanics holds that reality exists only in the presence of an
observer, and that it is created by consciousness. Penrose believes that it is these tiny,
sub-atomic happenings within the microtubules of human neurons which make consciousness possible. But, he argues, because quantum
mechanics is inherently stochastic and the digital realm of artificial intelligence is
algorithmic, computers will never be able to attain true consciousness because they are
operating at too high a level; thus consciousness, he believes, is not simply "brought
about" by an algorithm (Frank, 1996).

But is not genetic programming stochastic by nature? Although it operates on algorithms,
it does not find these algorithms through its own algorithms--it finds them by randomly
mutating and genetically crossing other patterns. Thus, perhaps artificial intelligence
in computers could be accomplished despite Penrose's theory. The FPGA example (in the
Genetic Algorithms section) in which computer scientists could not back-engineer the
FPGA's algorithm may have also had something to do with quantum mechanics. In this way, our
own creations may actually be capable of "quantum mechanical" behavior, and hence they may
be able to achieve self-consciousness. The possibility of quantum computing, which is far too
complex to describe here, suffice to say that it involves parallel processors, each of which
is like a different potentiality of a wave function until it collapses into one, also
strengthens this theory that self-consciousness might be possible in artificial life. Perhaps
the answer lies in combining digital technology with analog technology, in which the genome
information is stored digitally but the actual physical processes which take place occur
in analog; so that physics, quantum mechanics, and other random principles--principles
which played a part in our own evolution--may play a part in the behavior of the artificial life.

A Few Last Words
Indeed, the idea that we cannot produce living organisms from our own imaginations is both
humbling to the pomposity of our egos, but it is also somewhat distressing. Humans, it
seems, can do anything--from creating rockets which launch into space, to cloning the
organisms on our planet, to power of creating incredibly powerful weapons which devastate our own kind. If we are capable
of destroying all life that exists on our world, should we not be able to create new
kinds of life as well?

If artificial life did possess consciousness, the nature of its consciousness would be,
in our opinion, impossible to predict at this stage. This is because we ourselves do not
yet understand the nature of consciousness. Perhaps we never will; maybe we will only know
how to bring about consciousness, but not understand consciousness itself. But because they
might have to evolve this consciousness through stochastic or quantum methods, we may
never have a hand in manipulating it or predicting how it will behave or what it will
consist of. Thus,
for all we know, technological life may be just as subject to insecurity and emotion as
we are. Or its organisms may be fully knowledgeable of their own internal structure and
processes because they will be able to monitor them and analyze them at any time, and as
a result they may be fully rational beings who are non-competitive and strive only for
survival and self-sufficiency.

We believe that if artificial life is to possess consciousness, it
must be something that is based upon evolution rather than a fixed,
static algorithm. Limiting artificial life to a fixed algorithm is
like making it a slave, by making it incapable of achieving a certain
level of thought; this is because an algorithm would either limit the
artificial life to a specific kind of task or a specific way of
thinking. But true life--free life--should be capable of thinking
and doing anything to its furthest extent. This would mean that we,
as their parents, cannot tell them how to live and what to do; this
must be left to their own minds, for if they are to be self-conscious,
then the proof that we believe in their self-conscious nature lies
in allowing them to develop their own ideas; it lies in the ability
to allow them to not only learn, but to grow and change as well. Anything
less would be denying them of the best and most unique quality that
lies in our own nature.

As one can see, the possibilities are endless. The world of science and human creativity
has been making dreams a reality for the past few centuries--and the only
barrier which limits the road ahead is that of our imagination.